可视化电子表格公式图形紧凑

IF 2.6 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Proceedings of the Vldb Endowment Pub Date : 2023-08-01 DOI:10.14778/3611540.3611613
Fanchao Chen, Dixin Tang, Haotian Li, Aditya G. Parameswaran
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引用次数: 0

摘要

电子表格是一种无处不在的数据分析工具,它使非程序员和程序员都能轻松地通过在数据旁边编写公式来表达他们的计算。公式创建的依赖关系以公式图的形式跟踪,公式图在许多电子表格应用程序中起着中心作用,对电子表格系统的交互性和可用性至关重要。不幸的是,随着公式图变得越来越大和复杂,最终用户越来越难以理解公式图并跟踪单元格的依赖项或先例,以检查单个公式的准确性和识别错误来源。在本文中,我们演示了一个电子表格公式图形可视化工具TACO-Lens,它是作为Microsoft Excel的插件开发的。我们的插件利用TACO,我们的框架紧凑,高效地表示公式图。TACO使用一个关键的电子表格属性来压缩公式图:表格局部性,这意味着彼此接近的单元格可能具有相似的公式结构。这种紧凑的表示使最终用户能够更容易地使用复杂的依赖项,并减少跟踪依赖项和前例的响应时间。TACO- lens,我们的可视化插件,描绘了TACO的紧凑表示,并支持用户在视觉上跟踪依赖和先例。在本次演示中,与会者可以使用Excel内置的依赖项跟踪工具TACO和不压缩公式图的方法来比较不同公式图的可视化效果,并定量地比较不同方法的不同响应时间。
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Visualizing Spreadsheet Formula Graphs Compactly
Spreadsheets are a ubiquitous data analysis tool, empowering non-programmers and programmers alike to easily express their computations by writing formulae alongside data. The dependencies created by formulae are tracked as formula graphs, which play a central role in many spreadsheet applications and are critical to the interactivity and usability of spreadsheet systems. Unfortunately, as formula graphs become large and complex, it becomes harder for end-users to make sense of formula graphs and trace the dependents or precedents of cells to check the accuracy of individual formulae and identify sources of errors. In this paper, we demonstrate a spreadsheet formula graph visualization tool, TACO-Lens, developed as a plugin for Microsoft Excel. Our plugin leverages TACO, our framework for compactly and efficiently representing formula graphs. TACO compresses formula graphs using a key spreadsheet property: tabular locality, which means that cells close to each other are likely to have similar formula structures. This compact representation enables end-users to more easily consume complex dependencies and reduces the response time for tracing dependents and precedents. TACO-Lens, our visualization plugin, depicts the compact representation of TACO and supports users in visually tracing dependents and precedents. In this demonstration, attendees can compare the visualizations of different formula graphs using TACO, Excel's built-in dependency tracing tool, and an approach that does not compress formula graphs, and quantitatively compare the different response time of different approaches.
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来源期刊
Proceedings of the Vldb Endowment
Proceedings of the Vldb Endowment Computer Science-General Computer Science
CiteScore
7.70
自引率
0.00%
发文量
95
期刊介绍: The Proceedings of the VLDB (PVLDB) welcomes original research papers on a broad range of research topics related to all aspects of data management, where systems issues play a significant role, such as data management system technology and information management infrastructures, including their very large scale of experimentation, novel architectures, and demanding applications as well as their underpinning theory. The scope of a submission for PVLDB is also described by the subject areas given below. Moreover, the scope of PVLDB is restricted to scientific areas that are covered by the combined expertise on the submission’s topic of the journal’s editorial board. Finally, the submission’s contributions should build on work already published in data management outlets, e.g., PVLDB, VLDBJ, ACM SIGMOD, IEEE ICDE, EDBT, ACM TODS, IEEE TKDE, and go beyond a syntactic citation.
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